Deep multimodality models in image search ranking stack

Deep multimodality models in image search ranking stack

Rank Multimodal (RankMM) The RankMM model effectively combines the search paradigms of a text query, page context, and images to aid image and video retrieval. RankMM models are Visual Language (VL) models which take page context into account to improve image and video retrieval performance in a web-scale search engine.
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Enhancing Image Quality in Microsoft Bing

Enhancing Image Quality in Microsoft Bing

Enhancing image quality is a critical but challenging computer vision task. We've released a new AI-based model for improving the quality of images on Microsoft Bing. Not only are the Bing image search results relevant, but they are also beautiful and high-resolution. Our new V3 model outperformed the V2 model by 36% in terms of click-through rate, demonstrating that users find visually appealing images in search results more interesting and...
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Bing Releases Intelligent Question-Answering Feature to 100+ Languages

Bing Releases Intelligent Question-Answering Feature to 100+ Languages

Intelligent question-answering is one of the most useful and delightful features of search. As a user, you ask a question (e.g., “what are the benefits of eating apricots”) and can get the answer directly (e.g., info about health and nutrition benefits of apricots) at the top of the page without further need to search for relevant content by yourself. Recently, Bing expanded its intelligent question-answering feature to more than 100...
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Introducing the next wave of AI at Scale innovations in Bing

Introducing the next wave of AI at Scale innovations in Bing

Bing users around the globe perform hundreds of millions of search queries every day. These queries are diverse in many ways, from the intent the users are seeking to fulfill, to the languages and regions where these queries are issued. To handle such a dynamic range of usage, AI models in Bing must continuously evolve and therefore Bing is the prime example of Microsoft AI at Scale. This blog post introduces recent updates to Bing that are...
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Multi-granularity matching for Bing Image Search

Multi-granularity matching for Bing Image Search

Today we share more about continued evolution of Bing Image Search towards a more intelligent search engine through multi-granularity matches, improved understanding of user queries, images and webpages, as well as the relationships between them.
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Intelligent GIF Search: Finding the right GIF to express your emotions

This post describes the various machine learning techniques used in GIF search by Bing. To provide the best GIF search experience Bing employs techniques such as sentiment analysis, OCR, and even pose modeling of subjects appearing in GIF flicks to reflect subtle intent variations of your queries. Read on to find out more about how we made it work.
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